https://github.com/stanford-oval/genienlp
공식 코드Schema2QA: High-Quality and Low-Cost Q&A Agents for the Structured Web
Papers with Code 아카이브
Transfer Learning
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Transfer Learning is a machine learning technique where a model trained on one task is re-purposed and fine-tuned for a related, but different task. The idea behind transfer learning is to leverage the knowledge learned from a pre-trained model to solve a new, but related problem. This can be useful in situations where there is limited data available to train a new model from scratch, or when the new task is similar enough to the original task that the pre-trained model can be adapted to the new problem with only minor modifications.
<span style="color:grey; opacity: 0.6">( Image credit: Subodh Malgonde )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/stanford-oval/schema2qa
공식 코드Schema2QA: High-Quality and Low-Cost Q&A Agents for the Structured Web
https://github.com/stanford-oval/zero-shot-multiwoz-acl2020
공식 코드Zero-Shot Transfer Learning with Synthesized Data for Multi-Domain Dialogue State Tracking
https://github.com/stanfordmlgroup/MoCo-CXR
공식 코드MoCo-CXR: MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models
https://github.com/stanfordvl/sonicverse
공식 코드Sonicverse: A Multisensory Simulation Platform for Embodied Household Agents that See and Hear
https://github.com/star607/cross-city-mobility-transformer
공식 코드COLA: Cross-city Mobility Transformer for Human Trajectory Simulation
https://github.com/stardust-coder/japanese-lm-med-harness
공식 코드https://github.com/staruniversus/gcmae
공식 코드Global Contrast Masked Autoencoders Are Powerful Pathological Representation Learners
https://github.com/stasl0217/KEnS
공식 코드Multilingual Knowledge Graph Completion via Ensemble Knowledge Transfer
https://github.com/stasychbr/tnw-cate
공식 코드Heterogeneous Treatment Effect with Trained Kernels of the Nadaraya-Watson Regression
https://github.com/steffengra/anchoring_2
공식 코드A Multi-Task Approach to Robust Deep Reinforcement Learning for Resource Allocation
https://github.com/stepjam/RLBench
공식 코드RLBench: The Robot Learning Benchmark & Learning Environment
https://github.com/sthalles/carp
공식 코드Representation Learning via Consistent Assignment of Views over Random Partitions
https://github.com/sthalles/massl
공식 코드Learning from Memory: Non-Parametric Memory Augmented Self-Supervised Learning of Visual Features
https://github.com/sthowling/alioth
공식 코드https://github.com/stmcg/learner
공식 코드LEARNER: A Transfer Learning Method for Low-Rank Matrix Estimation
https://github.com/stmilab/cufflessbp_dann
공식 코드https://github.com/stoa-xh91/humandensepose
공식 코드KTN: Knowledge Transfer Network for Learning Multi-person 2D-3D Correspondences
https://github.com/stonybrooknlp/action-anticipation-lmtovideo
공식 코드https://github.com/strubell/LISA
공식 코드Linguistically-Informed Self-Attention for Semantic Role Labeling
https://github.com/stwhitfield/covid-severity
공식 코드Diagnosing COVID-19 Severity from Chest X-Ray Images Using ViT and CNN Architectures
https://github.com/subho406/OmniNet
공식 코드OmniNet: A unified architecture for multi-modal multi-task learning
https://github.com/suehiro93/mil_reduction
공식 코드https://github.com/sufe-nlp/transformer-alignment
공식 코드Accurate Word Alignment Induction from Neural Machine Translation
https://github.com/sulaimanvesal/CardiacQuanNet
공식 코드Spatio-temporal Multi-task Learning for Cardiac MRI Left Ventricle Quantification
https://github.com/suman101112/hasoc-fire-2020
공식 코드HASOCOne@FIRE-HASOC2020: Using BERT and Multilingual BERT models for Hate Speech Detection
https://github.com/sumn2u/garbage-classification-tl
공식 코드https://github.com/sumn2u/lulc-mapping
공식 코드Mapping of Land Use and Land Cover (LULC) using EuroSAT and Transfer Learning
https://github.com/sun-umn/Transfer-Learning-in-Medical-Imaging
공식 코드Rethinking Transfer Learning for Medical Image Classification
https://github.com/sun-umn/ttl
공식 코드Rethinking Transfer Learning for Medical Image Classification
https://github.com/sunanhe/mkt
공식 코드Open-Vocabulary Multi-Label Classification via Multi-Modal Knowledge Transfer
https://github.com/suncerock/EAsT-music-classification
공식 코드https://github.com/suncerock/peft-music
공식 코드Parameter-Efficient Transfer Learning for Music Foundation Models
https://github.com/sundw2014/DCM
공식 코드Knowledge Transfer via Dense Cross-Layer Mutual-Distillation
https://github.com/sungnyun/cav2vec
공식 코드Multi-Task Corrupted Prediction for Learning Robust Audio-Visual Speech Representation
https://github.com/sungwool/cfa_for_anomaly_localization
공식 코드CFA: Coupled-hypersphere-based Feature Adaptation for Target-Oriented Anomaly Localization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.